OpenRaiser/Intern-Atlas huggingface dataset:
Reconfiguration of Distributed Information Fusion System ? A case study
Venue: arXiv cs.DC 2009
Year: 2009

Information Fusion Systems are now widely used in different fusion contexts, like scientific processing, sensor networks, video and image processing. One of the current trends in this area is to cope with distributed systems. In this context, we have defined and implemented a Dynamic Distributed Information Fusion System runtime model. It allows us to cope with dynamic execution supports while trying to maintain the functionalities of a given Dynamic Distributed Information Fusion System. The paper presents our system, the reconfiguration problems we are faced with and our solutions.
On maximal repetitions of arbitrary exponent
Venue: arXiv cs.DM 2009
Year: 2009

The first two authors have shown [KK99,KK00] that the sum the exponent (and thus the number) of maximal repetitions of exponent at least 2 (also called runs) is linear in the length of the word. The exponent 2 in the definition of a run may seem arbitrary. In this paper, we consider maximal repetitions of exponent strictly greater than 1.
Design and Implementation of a High Quality and High Throughput TRNG in FPGA
Venue: arXiv cs.CR 2009
Year: 2009

This paper focuses on the design and implementation of a high-quality and high-throughput true-random number generator (TRNG) in FPGA. Various practical issues which we encountered are highlighted and the influence of the various parameters on the functioning of the TRNG are discussed. We also propose a few values for the parameters which use the minimum amount of the resources but still pass common random number generator test batteries such as DieHard and TestU01.
Global Stability Analysis for an Internet Congestion Control Model with a Time-Varying Link Capacity
Venue: arXiv cs.NI 2009
Year: 2009

In this paper, a global stability analysis is given for a rate-based congestion control system modeled by a nonlinear delayed differential equation. The model determines the dynamics of a single-source single-link network, with a time-varying capacity of link and a fixed communication delay. We obtain a sufficient delay-independent conditions on system parameters under which global asymptotic stability of the system is guarantied. The proof is based on an extension of Lyapunov-Krasovskii theorem for a class of nonlinear time-delay systems. The numerical simulations for a typical scenario justify the theoretical results.
Advances in the Design and Implementation of a Multi-Tier Architecture in the GIPSY Environment
Venue: arXiv cs.SE 2009
Year: 2009

We present advances in the software engineering design and implementation of the multi-tier run-time system for the General Intensional Programming System (GIPSY) by further unifying the distributed technologies used to implement the Demand Migration Framework (DMF) in order to streamline distributed execution of hybrid intensional-imperative programs using Java.
A genetic algorithm for structure-activity relationships: software implementation
Venue: arXiv cs.NE 2009
Year: 2009

The design and the implementation of a genetic algorithm are described. The applicability domain is on structure-activity relationships expressed as multiple linear regressions and predictor variables are from families of structure-based molecular descriptors. An experiment to compare different selection and survival strategies was designed and realized. The genetic algorithm was run using the designed experiment on a set of 206 polychlorinated biphenyls searching on structure-activity relationships having known the measured octanol-water partition coefficients and a family of molecular descriptors. The experiment shows that different selection and survival strategies create different partitions on the entire population of all possible genotypes.
Vision Based Navigation for a Mobile Robot with Different Field of Views
Venue: arXiv cs.RO 2009
Year: 2009

The basic idea behind evolutionary robotics is to evolve a set of neural controllers for a particular task at hand. It involves use of various input parameters such as infrared sensors, light sensors and vision based methods. This paper aims to explore the evolution of vision based navigation in a mobile robot. It discusses in detail the effect of different field of views for a mobile robot. The individuals have been evolved using different FOV values and the results have been recorded and analyzed.The optimum values for FOV have been proposed after evaluating more than 100 different values. It has been observed that the optimum FOV value requires lesser number of generations for evolution and the mobile robot trained with that particular value is able to navigate well in the environment.
Spread of Misinformation in Social Networks
Venue: arXiv cs.IT 2009
Year: 2009

We provide a model to investigate the tension between information aggregation and spread of misinformation in large societies (conceptualized as networks of agents communicating with each other). Each individual holds a belief represented by a scalar. Individuals meet pairwise and exchange information, which is modeled as both individuals adopting the average of their pre-meeting beliefs. When all individuals engage in this type of information exchange, the society will be able to effectively aggregate the initial information held by all individuals. There is also the possibility of misinformation, however, because some of the individuals are "forceful," meaning that they influence the beliefs of (some) of the other individuals they meet, but do not change their own opinion. The paper characterizes how the presence of forceful agents interferes with information aggregation. Under the assumption that even forceful agents obtain some information (however infrequent) from some others (and additional weak regularity conditions), we first show that beliefs in this class of societies converge to a consensus among all individuals. This consensus value is a random variable, however, and we characterize its behavior. Our main results quantify the extent of misinformation in the society by either providing bounds or exact results (in some special cases) on how far the consensus value can be from the benchmark without forceful agents (where there is efficient information aggregation). The worst outcomes obtain when there are several forceful agents and forceful agents themselves update their beliefs only on the basis of information they obtain from individuals most likely to have received their own information previously.
A Novel Two-Stage Dynamic Decision Support based Optimal Threat Evaluation and Defensive Resource Scheduling Algorithm for Multi Air-borne threats
Venue: arXiv cs.AI 2009
Year: 2009

This paper presents a novel two-stage flexible dynamic decision support based optimal threat evaluation and defensive resource scheduling algorithm for multi-target air-borne threats. The algorithm provides flexibility and optimality by swapping between two objective functions, i.e. the preferential and subtractive defense strategies as and when required. To further enhance the solution quality, it outlines and divides the critical parameters used in Threat Evaluation and Weapon Assignment (TEWA) into three broad categories (Triggering, Scheduling and Ranking parameters). Proposed algorithm uses a variant of many-to-many Stable Marriage Algorithm (SMA) to solve Threat Evaluation (TE) and Weapon Assignment (WA) problem. In TE stage, Threat Ranking and Threat-Asset pairing is done. Stage two is based on a new flexible dynamic weapon scheduling algorithm, allowing multiple engagements using shoot-look-shoot strategy, to compute near-optimal solution for a range of scenarios. Analysis part of this paper presents the strengths and weaknesses of the proposed algorithm over an alternative greedy algorithm as applied to different offline scenarios.
A new approach for digit recognition based on hand gesture analysis
Venue: arXiv cs.CV 2009
Year: 2009

We present in this paper a new approach for hand gesture analysis that allows digit recognition. The analysis is based on extracting a set of features from a hand image and then combining them by using an induction graph. The most important features we extract from each image are the fingers locations, their heights and the distance between each pair of fingers. Our approach consists of three steps: (i) Hand detection and localization, (ii) fingers extraction and (iii) features identification and combination to digit recognition. Each input image is assumed to contain only one person, thus we apply a fuzzy classifier to identify the skin pixels. In the finger extraction step, we attempt to remove all the hand components except the fingers, this process is based on the hand anatomy properties. The final step consists on representing histogram of the detected fingers in order to extract features that will be used for digit recognition. The approach is invariant to scale, rotation and translation of the hand. Some experiments have been undertaken to show the effectiveness of the proposed approach.
Geometrical Interpretation of the Master Theorem for Divide-and-conquer Recurrences
Venue: arXiv cs.DS 2009
Year: 2009

We provide geometrical interpretation of the Master Theorem to solve divide-and-conquer recurrences. We show how different cases of the recurrences correspond to different kinds of fractal images. Fractal dimension and Hausdorff measure are shown to be closely related to the solution of such recurrences.
TTSS Packet Classification Algorithm to enhance Multimedia Applications in Network Processor based Router
Venue: arXiv cs.MM 2009
Year: 2009

The objective of this paper is to implement the Trie based Tuple Space Search(TTSS) packet classification algorithm for Network Processor(NP) based router to enhance multimedia applications. The performance is evaluated using Intel IXP2400 NP Simulator. The results demonstrate that, TTSS has better performance than Tuple Space Search algorithm and is well suited to achieve high speed packet classification to support multimedia applications.
Online Reinforcement Learning for Dynamic Multimedia Systems
Venue: arXiv cs.LG 2009
Year: 2009

In our previous work, we proposed a systematic cross-layer framework for dynamic multimedia systems, which allows each layer to make autonomous and foresighted decisions that maximize the system's long-term performance, while meeting the application's real-time delay constraints. The proposed solution solved the cross-layer optimization offline, under the assumption that the multimedia system's probabilistic dynamics were known a priori. In practice, however, these dynamics are unknown a priori and therefore must be learned online. In this paper, we address this problem by allowing the multimedia system layers to learn, through repeated interactions with each other, to autonomously optimize the system's long-term performance at run-time. We propose two reinforcement learning algorithms for optimizing the system under different design constraints: the first algorithm solves the cross-layer optimization in a centralized manner, and the second solves it in a decentralized manner. We analyze both algorithms in terms of their required computation, memory, and inter-layer communication overheads. After noting that the proposed reinforcement learning algorithms learn too slowly, we introduce a complementary accelerated learning algorithm that exploits partial knowledge about the system's dynamics in order to dramatically improve the system's performance. In our experiments, we demonstrate that decentralized learning can perform as well as centralized learning, while enabling the layers to act autonomously. Additionally, we show that existing application-independent reinforcement learning algorithms, and existing myopic learning algorithms deployed in multimedia systems, perform significantly worse than our proposed application-aware and foresighted learning methods.
Encapsulation and Dynamic Modularity in the Pi-Calculus
Venue: arXiv cs.PL 2009
Year: 2009

We describe a process calculus featuring high level constructs for component-oriented programming in a distributed setting. We propose an extension of the higher-order pi-calculus intended to capture several important mechanisms related to component-based programming, such as dynamic update, reconfiguration and code migration. In this paper, we are primarily concerned with the possibility to build a distributed implementation of our calculus. Accordingly, we define a low-level calculus, that describes how the high-level constructs are implemented, as well as details of the data structures manipulated at runtime. We also discuss current and future directions of research in relation to our analysis of component-based programming.
Theory of Rule 6 and its Application to Round Robin Tournament
Venue: arXiv cs.DM 2009
Year: 2009

In this paper we have used one 2 variable Boolean function called Rule 6 to define another beautiful transformation named as Extended Rule-6. Using this function we have explored the algebraic beauties and its application to an efficient Round Robin Tournament (RRT) routine for 2k (k is any natural number) number of teams. At the end, we have thrown some light towards any number of teams of the form nk where n, k are natural numbers.
XDANNG: XML based Distributed Artificial Neural Network with Globus Toolkit
Venue: arXiv cs.NE 2009
Year: 2009

Artificial Neural Network is one of the most common AI application fields. This field has direct and indirect usages most sciences. The main goal of ANN is to imitate biological neural networks for solving scientific problems. But the level of parallelism is the main problem of ANN systems in comparison with biological systems. To solve this problem, we have offered a XML-based framework for implementing ANN on the Globus Toolkit Platform. Globus Toolkit is well known management software for multipurpose Grids. Using the Grid for simulating the neuron network will lead to a high degree of parallelism in the implementation of ANN. We have used the XML for improving flexibility and scalability in our framework.
Degenerate neutrality creates evolvable fitness landscapes
Venue: arXiv cs.NE 2009
Year: 2009

Understanding how systems can be designed to be evolvable is fundamental to research in optimization, evolution, and complex systems science. Many researchers have thus recognized the importance of evolvability, i.e. the ability to find new variants of higher fitness, in the fields of biological evolution and evolutionary computation. Recent studies by Ciliberti et al (Proc. Nat. Acad. Sci., 2007) and Wagner (Proc. R. Soc. B., 2008) propose a potentially important link between the robustness and the evolvability of a system. In particular, it has been suggested that robustness may actually lead to the emergence of evolvability. Here we study two design principles, redundancy and degeneracy, for achieving robustness and we show that they have a dramatically different impact on the evolvability of the system. In particular, purely redundant systems are found to have very little evolvability while systems with degeneracy, i.e. distributed robustness, can be orders of magnitude more evolvable. These results offer insights into the general principles for achieving evolvability and may prove to be an important step forward in the pursuit of evolvable representations in evolutionary computation.
Strategic Positioning in Tactical Scenario Planning
Venue: arXiv cs.NE 2009
Year: 2009

Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for optimization that has not been explored in great detail and involves a number of interesting challenges which are distinct from traditional optimization research. Planning problems demand solutions that can satisfy a number of competing objectives on multiple scales related to robustness, adaptiveness, risk, etc. The scenario method is a key approach for planning. Scenarios can be defined for long-term as well as short-term plans. This paper introduces computational scenario-based planning problems and proposes ways to accommodate strategic positioning within the tactical planning domain. We demonstrate the methodology in a resource planning problem that is solved with a multi-objective evolutionary algorithm. Our discussion and results highlight the fact that scenario-based planning is naturally framed within a multi-objective setting. However, the conflicting objectives occur on different system levels rather than within a single system alone. This paper also contends that planning problems are of vital interest in many human endeavors and that Evolutionary Computation may be well positioned for this problem domain.
Agent-Oriented Approach for Detecting and Managing Risks in Emergency Situations
Venue: arXiv cs.AI 2009
Year: 2009

This paper presents an agent-oriented approach to build a decision support system aimed at helping emergency managers to detect and to manage risks. We stress the flexibility and the adaptivity characteristics that are crucial to build a robust and efficient system, able to resolve complex problems. The system should be independent as much as possible from the subject of study. Thereby, an original approach based on a mechanism of perception, representation, characterisation and assessment is proposed. The work described here is applied on the RoboCupRescue application. Experimentations and results are provided.
Credit Assignment in Adaptive Evolutionary Algorithms
Venue: arXiv cs.NE 2009
Year: 2009

In this paper, a new method for assigning credit to search operators is presented. Starting with the principle of optimizing search bias, search operators are selected based on an ability to create solutions that are historically linked to future generations. Using a novel framework for defining performance measurements, distributing credit for performance, and the statistical interpretation of this credit, a new adaptive method is developed and shown to outperform a variety of adaptive and non-adaptive competitors.
Robustness and Adaptiveness Analysis of Future Fleets
Venue: arXiv cs.NE 2009
Year: 2009

Making decisions about the structure of a future military fleet is a challenging task. Several issues need to be considered such as the existence of multiple competing objectives and the complexity of the operating environment. A particular challenge is posed by the various types of uncertainty that the future might hold. It is uncertain what future events might be encountered; how fleet design decisions will influence and shape the future; and how present and future decision makers will act based on available information, their personal biases regarding the importance of different objectives, and their economic preferences. In order to assist strategic decision-making, an analysis of future fleet options needs to account for conditions in which these different classes of uncertainty are exposed. It is important to understand what assumptions a particular fleet is robust to, what the fleet can readily adapt to, and what conditions present clear risks to the fleet. We call this the analysis of a fleet's strategic positioning. This paper introduces how strategic positioning can be evaluated using computer simulations. Our main aim is to introduce a framework for capturing information that can be useful to a decision maker and for defining the concepts of robustness and adaptiveness in the context of future fleet design. We demonstrate our conceptual framework using simulation studies of an air transportation fleet. We capture uncertainty by employing an explorative scenario-based approach. Each scenario represents a sampling of different future conditions, different model assumptions, and different economic preferences. Proposed changes to a fleet are then analysed based on their influence on the fleet's robustness, adaptiveness, and risk to different scenarios.
Induction of Word and Phrase Alignments for Automatic Document Summarization
Venue: arXiv cs.CL 2009
Year: 2009

Current research in automatic single document summarization is dominated by two effective, yet naive approaches: summarization by sentence extraction, and headline generation via bag-of-words models. While successful in some tasks, neither of these models is able to adequately capture the large set of linguistic devices utilized by humans when they produce summaries. One possible explanation for the widespread use of these models is that good techniques have been developed to extract appropriate training data for them from existing document/abstract and document/headline corpora. We believe that future progress in automatic summarization will be driven both by the development of more sophisticated, linguistically informed models, as well as a more effective leveraging of document/abstract corpora. In order to open the doors to simultaneously achieving both of these goals, we have developed techniques for automatically producing word-to-word and phrase-to-phrase alignments between documents and their human-written abstracts. These alignments make explicit the correspondences that exist in such document/abstract pairs, and create a potentially rich data source from which complex summarization algorithms may learn. This paper describes experiments we have carried out to analyze the ability of humans to perform such alignments, and based on these analyses, we describe experiments for creating them automatically. Our model for the alignment task is based on an extension of the standard hidden Markov model, and learns to create alignments in a completely unsupervised fashion. We describe our model in detail and present experimental results that show that our model is able to learn to reliably identify word- and phrase-level alignments in a corpus of <document,abstract> pairs.
Attacking the combination generator
Venue: arXiv cs.CR 2009
Year: 2009

We present one of the most efficient attacks against the combination generator. This attack is inherent to this system as its only assumption is that the filtering function has a good autocorrelation. This is usually the case if the system is designed to be resistant to other kinds of attacks. We use only classical tools, namely vectorial correlation, weight 4 multiples and Walsh transform.
A class of structured P2P systems supporting browsing
Venue: arXiv cs.IR 2009
Year: 2009

Browsing is a way of finding documents in a large amount of data which is complementary to querying and which is particularly suitable for multimedia documents. Locating particular documents in a very large collection of multimedia documents such as the ones available in peer to peer networks is a difficult task. However, current peer to peer systems do not allow to do this by browsing. In this report, we show how one can build a peer to peer system supporting a kind of browsing. In our proposal, one must extend an existing distributed hash table system with a few features : handling partial hash-keys and providing appropriate routing mechanisms for these hash-keys. We give such an algorithm for the particular case of the Tapestry distributed hash table. This is a work in progress as no proper validation has been done yet.